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Predicting the Construction of New Highway Links

Author

Listed:
  • David Levinson

    (Nexus (Networks, Economics, and Urban Systems) Research Group, Department of Civil Engineering, University of Minnesota)

  • Ramachandra Karamalaputi

Abstract

This paper examines new highway construction based on the status of the network, traffic demand, project costs, and budget constraints. The data span two decades and consist of descriptions of physical attributes of the network, the construction and expansion history, and average annual daily traffic values on each of the links. An algorithm is developed to designate adjacent and parallel links in a large network. A nonlinear cost model for new construction and highway expansion is developed for the Minneapolis-St. Paul metropolitan area. Results show that new links providing greater potential access are more likely to be constructed and that more links will be constructed when the budget is larger, which supports the underlying economic theory. The models developed here have important implications for planning and forecasting, allowing us to predict how networks might be altered in the future in response to changing conditions.

Suggested Citation

  • David Levinson & Ramachandra Karamalaputi, 2003. "Predicting the Construction of New Highway Links," Working Papers 200305, University of Minnesota: Nexus Research Group.
    • Handle: RePEc:nex:wpaper:newconstruction
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    File URL: http://hdl.handle.net/11299/179909
    File Function: First version, 2007
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    References listed on IDEAS

    as
    1. Noland, Robert B., 2001. "Relationships between highway capacity and induced vehicle travel," Transportation Research Part A: Policy and Practice, Elsevier, vol. 35(1), pages 47-72, January.
    2. Brownstone, David & Train, Kenneth, 1998. "Forecasting new product penetration with flexible substitution patterns," Journal of Econometrics, Elsevier, vol. 89(1-2), pages 109-129, November.
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    6. David Levinson & Ramachandra Karamalaputi, 2003. "Induced Supply: A Model of Highway Network Expansion at the Microscopic Level," Journal of Transport Economics and Policy, University of Bath, vol. 37(3), pages 297-318, September.
    7. Bhat, Chandra R., 2001. "Quasi-random maximum simulated likelihood estimation of the mixed multinomial logit model," Transportation Research Part B: Methodological, Elsevier, vol. 35(7), pages 677-693, August.
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    Full references (including those not matched with items on IDEAS)

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    Cited by:

    1. Martin, Juan Carlos & García-Palomares, Juan Carlos & Gutierrez, Javier & Román, Concepción, 2010. "Efficiency and equity of orbital motorways in Madrid," The Journal of Transport and Land Use, Center for Transportation Studies, University of Minnesota, vol. 3(1), pages 67-84.
    2. Yossi Berechman & Bekir Bartin & Ozlem Yanmaz-Tuzel & Kaan Ozbay, 2011. "The Full Marginal Costs of Highway Travel: Methods and Empirical Estimation for North America," Chapters, in: André de Palma & Robin Lindsey & Emile Quinet & Roger Vickerman (ed.), A Handbook of Transport Economics, chapter 19, Edward Elgar Publishing.
    3. Irene Casas & Amit Malik & Eric Delmelle & Mark Karwan & Rajan Batta, 2007. "An Automated Network Generation Procedure for Routing of Unmanned Aerial Vehicles (UAVs) in a GIS Environment," Networks and Spatial Economics, Springer, vol. 7(2), pages 153-176, June.
    4. Weber, Joe, 2018. "Route change on the American freeway system," Journal of Transport Geography, Elsevier, vol. 67(C), pages 12-23.

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    More about this item

    JEL classification:

    • R41 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Transportation: Demand, Supply, and Congestion; Travel Time; Safety and Accidents; Transportation Noise
    • R42 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Government and Private Investment Analysis; Road Maintenance; Transportation Planning
    • R48 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Government Pricing and Policy
    • D10 - Microeconomics - - Household Behavior - - - General
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes

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